Concept

Electrodiagnostic medicine

Publications associées (34)

Early decoding of walking tasks with minimal set of EMG channels

Silvestro Micera, Francesco Iberite, Federica Barberi, Eugenio Anselmino

Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decod ...

IOP Publishing Ltd2023

Structure-function coupling increases during interictal spikes in temporal lobe epilepsy: A graph signal processing study

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Patric Hagmann

Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). Methods: We decomposed IEDs of 17 pati ...

ELSEVIER IRELAND LTD2023

Plasticity of sensory representations in the posterior insular cortex during fear learning

Denys Osypenko

Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...

EPFL2023

Breathing is coupled with voluntary initiation of mental imagery

Olaf Blanke, Oliver Alan Kannape, Hyeongdong Park

Previous research has suggested that bodily signals from internal organs are associated with diverse cortical and subcortical processes involved in sensory-motor functions, beyond homeostatic reflexes. For instance, a recent study demonstrated that the pre ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Resting-State Brain Activity for Early Prediction Outcome in Postanoxic Patients in a Coma with Indeterminate Clinical Prognosis

Dimitri Nestor Alice Van De Ville

The authors used resting-state fMRI in a prospective study to compare whole-brain functional connectivity between patients with good and poor outcomes, implementing support vector machine learning. They automatically predicted coma outcome using resting-st ...

AMER SOC NEURORADIOLOGY2020

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Damián Pascual Ortiz

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...

2020

Neural Correlates of Reinforcement Learning: eligibility trace, reward prediction error, novelty and surprise

He Xu

In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can obtain from an environment. During learning, the actual and expected outcomes are compared to tell whether a decision was good or bad. The difference between ...

EPFL2020

A Adaptive Algorithm for Online Interference Cancellation in EMG Sensors

Hakan Gökcesu, Kaan Gökcesu

One of the biggest issues encountered in the analysis of sensitive electromyography (EMG) sensor data is the power line interference (PLI). Conventional methods in literature either lose valuable sensor data or inadequately decrease the power line noise. I ...

2019

Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI

João Pedro Forjaco Jorge

Simultaneous EEG-fMRI allows multiparametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data se ...

2019

Reach-to-grasp motions: Towards a dynamic classification approach for upper-limp prosthesis

Aude Billard, Iason Batzianoulis

During reach-to-grasp motions,the Electromyographic (EMG) activity of the arm varies depending on motion stage. The variability of the EMG signals results in low classification accuracy during the reaching phase, delaying the activation of the prosthesis. ...

IEEE2019

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